PhD Scholarship on Multi-criteria Decision-Making and Optimisation at the University of Manchester, UK

PhD Scholarship on Multi-criteria Decision-Making and Optimisation at the
University of Manchester, UK

This PhD scholarship offers three years’ funding, including tuition fees and
annual stipend of approximately £15,000 for candidates commencing their studies
in September 2018. The successful candidate will receive a generous research
support and conference allowance, and have access to a robust doctoral research
training programme, dedicated research resources, training in transferable
skills, visiting speaker seminar programme, and associate with existing
research centres and groups. Students are encouraged to undertake training and
development in teaching and deliver teaching/research assistantship duties on a
paid basis to further enhance their experience in preparation for their future
careers.

The Project
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In many strategic problems in logistics, managements, planning, and
manufacturing, a Decision Maker (DM) must find solutions that optimise
multiple, conflicting criteria and decide among them, which nowadays often
involves the DM interacting with some automated process implemented as a
Multi-criteria Decision-Making and Optimisation (MCDMO) algorithm. In reality,
decision-making is influenced by human factors (cognitive biases, fatigue,
mistakes) that have been thoroughly studied in behavioural economics and
psychology. The design of algorithms able to cope with these human factors
remains an open challenge.

This project aims to devise realistic, general “simulations” of DMs (machine
DMs) that explicitly model these human factors as configurable parameters,
independent of specific preferences. Machine DMs will enable the empirical
analysis of algorithms with respect to particular human factors. Parameters of
machine DMs may be explicitly set to mimic human behaviours (e.g. risk-averse
vs. risk-seeking). The ultimate goal is the development of the next generation
of data analytics and decision support methods that adapt to the human factors
prominent on particular problem scenarios, thus helping humans to make better
decisions.

Entry Requirements
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Applications are sought from exceptional UK, EU and international students with
an outstanding academic background, ideally in Computer Science, Mathematics,
Operations Research, Data Science, Business Analytics, Industrial Engineering,
Economics, or other discipline within business and operations management. The
successful candidate must have a strong programming background
(C/C++/Java/R/Python) and good analytical and communication skills. An
understanding of multi-criteria decision-making and/or mathematical and
heuristic multi-objective optimization techniques is highly desirable.